Assessing biodiversity with species accumulation curves; inventories of small reptiles by pit‐trapping in Western Australia

Abstract We examined 11 non‐linear regression models to determine which of them best fitted curvilinear species accumulation curves based on pit‐trapping data for reptiles in a range of heterogeneous and homogenous sites in mesic, semi‐arid and arid regions of Western Australia. A well‐defined plateau in a species accumulation curve is required for any of the models accurately to estimate species richness. Two different measures of effort (pit‐trapping days and number of individuals caught) were used to determine if the measure of effort influenced the choice of the best model(s). We used species accumulation curves to predict species richness, determined the trapping effort required to catch a nominated percentage (e.g. 95%) of the predicted number of species in an area, and examined the relationship between species accumulation curves with diversity and rarity. Species richness, diversity and the proportion of rare species in a community influenced the shape of species accumulation curves. The Beta‐P model provided the best overall fit (highest r²) for heterogeneous and homogeneous sites. For heterogeneous sites, Hill, Rational, Clench, Exponential and Weibull models were the next best. For homogeneous habitats, Hill, Weibull and Chapman–Richards were the next best models. There was very little difference between Beta‐P and Hill models in fitting the data to accumulation curves, although the Hill model generally over‐estimated species richness. Most models worked equally well for both measures of trapping effort. Because the number of individuals caught was influenced by both pit‐trapping effort and the abundance of individuals, both measures of effort must be considered if species accumulation curves are to be used as a planning tool. Trapping effort to catch a nominated percentage of the total predicted species in homogeneous and heterogeneous habitats varied among sites, but even for only 75% of the predicted number of species it was generally much higher than the typical effort currently being used for terrestrial vertebrate fauna surveys in Australia. It was not possible to provide a general indication of the effort required to predict species richness for a site, or to capture a nominated proportion of species at a site, because species accumulation curves are heavily influenced by the characteristics of particular sites.     

Recording effort biases the species richness cited in plant distribution atlases

This paper explores potential biases due to recording effort in the species richness (number of vascular plant species) recorded in grid-mapping projects. In this study, we review 80 regional and national grid Central European Basic Area (CEBA) mapping projects on the vascular plant flora of Central Europe. The measures of recording effort used were the duration of the mapping project, resolution of the mapping grid and number of botanists involved. Furthermore, several environmental and geographic factors associated with the variation in species richness were used as covariables: the number of phytosociological units in the Map of Potential Natural Vegetation of Europe, altitudinal range, annual precipitation, mean January and June temperatures and geographical location of the study areas. The effects of individual factors on species richness were compared by multiple regression and hierarchical partitioning. Both methods indicated a bias in observed species richness due to recording effort. Multiple regression indicated a significant role of duration of study, and hierarchical partitioning revealed significant effects of duration, number of botanists and used resolution. Of the variation in the total number of species recorded, 8% was attributed to the duration of mapping, 9% to the used resolution, and 7% to the number of botanists involved in mapping. However, this bias was scale-dependent. Although the sampling effect can be neglected on a broad scale, on a finer scale a significant amount of the variation in plant species richness can be ascribed to recording effort. This indicates the need for a standard approach in mapping and analysing patterns of species richness.     

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as “species accumulation data”). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species accumulation data. We use estimators of population size that were developed for capture‐recapture data, but that can be used to estimate the size of species assemblages using species accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to of use capture‐recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.     

Determining adequate trapping effort and species richness using species accumulation curves for environmental impact assessments

Abstract Environmental impact assessments (EIA) require that the proponent indicates the potential impact that a development will have on the biodiversity of the area. As part of this assessment it is normal practice to inventory the vertebrate species in the area. We show here how species accumulation curves can be used as a tool by environmental consultants to indicate the adequacy of their trapping effort and predict species richness for a disturbance site. The shape of a species accumulation curve is influenced by the number of species in an assemblage and the proportional number of singletons (rarely caught species) in the survey sample. We provide guidelines for the number of individuals that need to be caught in a trapping program to achieve 80% and 90% of the species in a habitat, and we indicate how this number can be adjusted to accommodate variations in relative species abundance.     

Bayesian image restoration models for combining expert knowledge on recording activity with species distribution data

Biological atlases are, for many species, the only source of information on their distribution over large geographical areas, and are widely used to inform models of the environmental distribution of species. Such data are not collected using standardized survey techniques, however, and spatial variations in coverage (the relative extent or completeness of records) may lead to variations in the probability that the species will be recorded at locations where it is present (the “recording probability”). If spatial patterns in recording probabilities are correlated with key environmental variables, then biased estimates of the relationships between environmental variables and species distributions may be obtained. We outline a general statistical framework for modelling the environmental distribution of species using, known as Bayesian Image Restoration (BIR). BIR can be used in combination with any species distribution model, but in addition allows us to account for spatial heterogeneity in recording probabilities by utilizing expert knowledge on spatial patterns in coverage. We illustrate the methodology by applying it to maps of the recorded distribution of two plant species in Germany, taken from the German atlas of vascular plants. We find that estimated spatial patterns in recording probabilities for both species are correlated with key environmental variables. Consequently, different relationships between the probability of presence of a species and environmental variables were obtained when the species distribution models were parameterised within a BIR framework. Care must be taken in the application of BIR, since the resulting inferences can depend strongly upon the modelling assumptions that are adopted. Nevertheless, we conclude that BIR has the potential to make better use of uncertain information on species distributions than conventional methods, and can be used to formally investigate the robustness of inferences on the environmental distribution of species to assumptions concerning spatial patterns in recording probabilities.     

Variation in incubation effort during egg laying in the Mountain Bluebird and its association with hatching asynchrony

Females in many bird species reportedly begin incubation prior to clutch completion, but the nature of such incubation and the degree to which it varies among females remains undescribed for almost all species. We used continuous recording of nest‐cup temperatures to document incubation effort during egg laying at 57 Mountain Bluebird (Sialia currucoides) nests in a high‐elevation Wyoming population. We then asked whether such effort predicted the degree to which eggs hatch asynchronously. Although substantial egg heating could begin abruptly late in laying (previously reported as the norm for this species) or even after clutch completion, we found that most (>90%) females began incubation gradually, engaging in a few (usually 1–8), brief (<10 min) bouts of heating on the day they laid their first or second egg. Thereafter, females varied markedly in when they increased incubation effort and by how much. The onset of nocturnal incubation also varied, with females beginning to incubate at night after laying their prepenultimate, penultimate, or last egg and not always initially incubating through the night. As an index of the total amount of heat applied to eggs during laying, we calculated the cumulative number of degrees by which nest‐cup temperatures exceeded the threshold temperature required for embryonic development. This value varied by more than 150‐fold between nests and explained >50% of the variation in hatching asynchrony. Our results thus provide strong support for the widely held, but rarely tested, assumption that parent birds can have substantial control over the degree of hatching asynchrony by varying the amount of incubation done prior to clutch completion.     

Backpack electrofishing effort and imperfect detection: Influence on riverine fish inventories and monitoring

An increased electrofishing sampling effort will increase detection probabilities of riverine fishes. In this study, a repeat‐sampling approach was used in small to medium‐sized Ontario (Canada) rivers to estimate: (i) species‐specific detection probabilities of freshwater fishes, (ii) the number of sampling events required to confidently detect species, and (iii) the power of timed‐search surveys to detect future distribution (or occupancy) declines. Wadeable habitats at 36 sites were sampled with a backpack electrofisher on four separate dates during the summer low‐flow period in 2013 and 2014. Forty‐two species were collected, including three species of conservation concern (American eel Anguilla rostrata Lacépède, 1802, channel darter Percina copelandi Jordan, 1877, northern sunfish Lepomis peltastes Cope, 1870), and two recreationally important species (largemouth bass Micropterus salmoides Lacépède, 1802 and smallmouth bass Micropterus dolomieu Lacépède, 1802). A hierarchical Bayesian modelling approach was used to estimate detection probabilities and site occupancy for 18 species at four levels of effort: 250, 500, 750 and 1,000 s. In all cases, species detection was imperfect. Search effort had a positive effect on estimates of detection probability and site occupancy and the power to detect declines in future distribution. Detection probabilities ranged from 0.11 to 0.66 with an effort of 250 s, and 0.27 to 0.92 with an effort of 1,000 s. For 13 species, detection and power to detect changes in distribution were significantly improved by increasing sampling effort from 250 to 750 s or 1,000 s. For the channel darter and northern sunfish, three replicate sampling visits (of 750 or 1,000 s duration) are recommended for confident detection.     

Optimising sampling methods for small mammal communities in Neotropical rainforests

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Assessing the completeness of bryophytes inventories: an oceanic island as a case study (Terceira,Azorean archipelago)

How useful, complete or unbiased are comprehensive databases in order to provide reliable estimations of diversity? Using compiled data from bryophytes in Terceira Island (Azores), we specifically aim (1) to describe the register of species over time, (2) to assess the inventory completeness, i.e., the ratio between the observed and the maximum expected species, and (3) to locate the most promising areas for further surveys. First, each new recorded species was plotted against its collecting year, using the number of database-records as a surrogate of survey effort, to get the accumulation curves. These curves were then extrapolated to obtain the theoretical number of existing species according to Clench and exponential models. Spatial and habitat characteristics of the recorded taxa were also explored. Our results show an increasing trend in the rate of recorded species (c. five species per year), as well as a maximum of around a third of the theoretically “real” number of expected species that could yet remain unknown. Nevertheless, predictions of species richness were highly variable depending on the fitting curve used. Survey effort was similar between liverworts and mosses, as were inventory completeness values, but the rate of new recorded species was higher for mosses. Although bryologists visited preferably native habitats, we show that new species citations may also be found in modified habitats (e.g., exotic forests and semi-natural grasslands). We conclude that the analysis of extensive databases is a useful tool in revealing the recording and taxonomic gaps, further showing that bryophyte inventories could still be incomplete in Terceira Island. A strategy on how to improve species’ collections in remote areas is suggested, hoping to contribute to all-inclusive biodiversity studies in the Azores and elsewhere.     

Towards the automated detection and occupancy estimation of primates using passive acoustic monitoring

Recent advancements in technology have made possible the use of novel, cost-efficient biomonitoring techniques which facilitate monitoring animal populations at larger spatial and temporal scales. Here, we investigated using passive acoustic monitoring (PAM) for wild primate populations living in the forest of Taï National Park, Côte d’Ivoire. We assessed the potential of using a customized algorithm for the automated detection of multiple primate species to obtain reliable estimates of species occurrence from acoustic data. First, we applied the algorithm on continuous rainforest recordings collected using autonomous recording units (ARUs) to detect and classify three sound signals: chimpanzee buttress drumming, and the loud calls of the diana and king colobus monkey. Using an occupancy modelling approach we then investigated to what extent the automated, probabilistic output needs to be listened to, and thus manually cleaned, by a human expert, to approach occupancy probabilities derived from ARU data fully verified by a human. To do this we explored the robustness of occupancy probability estimates by simulating ARU datasets with various degrees of cleaning for false positives and false negative detections. We further validated the approach by comparing it to data collected by human observers on point transects located within the same study area. Our study demonstrates that occurrence estimates from ARU data, combined with automated processing methods such as our algorithm, can provide results comparable to data collected by humans and require less effort. We show that occupancy probabilities are quite robust to cleaning effort, particularly when occurrence is high, and suggest that for some species even naïve occupancy, as derived from ARU data without any cleaning, could provide a quick and reliable indicator to guide monitoring efforts. We found detection probabilities to be most influenced by time of day for chimpanzee drums while temperature and, likely, poaching pressure, affected detection of diana monkey loud calls. None of the covariates investigated appeared to have strongly affected king colobus loud call detection. Finally, we conclude that the semi-automated approach presented here could be used as an early-warning system for poaching activity and suggest additional techniques for improving its performance.     

Temporal Patterns of Species Accumulation in a Survey of Lepidoptera in a Beech-Maple Forest

One of the most significant challenges to insect conservation is lack of information concerning species diversity and distribution. Because a complete inventory of all species in an area is virtually impossible, interest has turned to developing statistical techniques to guide sampling design and to estimate total species richness within a site. We used two such techniques, diversity partitioning and non-parametric richness estimation, to determine how variation in sampling effort over time affected species accumulation for a survey of Lepidoptera in an old-growth beech-maple forest. Temporal scaling of sampling effort had significant effects on two measures of species diversity. Increases in species richness were primarily driven by changes in species occurrences with season, while Shannon diversity was largely determined at the scale of individual sampling units (i.e. by spatial effects). Variation in sampling effort affected the values of the two most widely regarded richness estimators (ICE and Chao 2); neither diversity estimator achieved stable values across a range of sampling efforts. Even after 52 trap-nights and accounting for seasonality, rare species (singletons and uniques) remained a significant component of the moth community. To the extent that moth communities in other forest systems are similarly comprised of many rare species, non-parametric richness estimators should be expected to yield variable estimates with increased effort and should only be used to provide a minimum benchmark for predicting the number of species remaining to be sampled. Our results suggest the best strategy for a short-term survey of forest Lepidoptera should emphasize spreading sampling intervals throughout a given year rather than focusing on intensive sampling during a short time period or prolonged sampling over many years.     

When have we looked hard enough? A novel method for setting minimum survey effort protocols for flora surveys

There is now a substantial body of literature documenting the detectability of plants and animals under standard survey conditions. Despite the evidence that many flora and fauna species have detection probabilities of less than one, it is still the default assumption of most environmental impact assessment processes that if a species is present, it will be detected. Here we briefly review a number of existing studies that have estimated the survey effort necessary to detect animal species, based on what is known about their detection rates in standard surveys. We then propose a novel method, based on failure‐time analysis, for quantifying the detectability of and determining appropriate survey effort for plant species during flora surveys. We provide computer code for implementing the method in the Bayesian freeware WinBUGS. Methods for estimating detectability can be used to inform minimum survey requirements and have important applications in environmental impact assessment and monitoring.     

Willow grouse bag size is more sensitive to variation in hunter effort than to variation in willow grouse density

Annual variation in harvested animals (hereafter bag size) is often used as an index of population abundance when investigating population dynamics. Few studies have evaluated how well bag size tracks population change despite its widespread use. Two recent studies on grouse harvest statistics have reached contrasting conclusions. Th ere is limited information about the functional response of hunters in relation to varying game densities, and effort is seldom recorded. We investigated how much of the variation in bag size (total number of harvested grouse km^?2) is explained by variation in willow grouse Lagopus lagopus density (adult and young grouse km^?2) and hunting eff ort (total number of hunting days km^?2). We also evaluated catch per unit effort (CPUE) as an index of grouse abundance, and estimated the response in harvest rate (total bag size in relation to total grouse density) to varying hunting effort. We used data from the 88 management areas on state land in Jämtland county, Sweden (1996–2007), where hunting days and bag size are recorded in detail. Willow grouse density was estimated in four of these management areas in August using line transects and distance sampling. The hunting effort and total grouse density explained most of the variation in bag size (R²= 0.89). Bag size was twice as sensitive to changes in hunting effort compared to changes in grouse density. More than a ten times change in the grouse population density was required to one unit change in bag size. The use of CPUE did not provide a better alternative index of grouse density, and variation in density only explained 23% of the variation in CPUE. Harvest rate showed a strong relationship with hunting effort, and we suggest that an upper limit in hunting effort can be used to reduce the risk of high harvest rates. Hunters became more efficient at low densities and controlling hunting effort is most important when there are indications of population lows and/or poor breeding. CPUE may be less sensitive to changes in game abundance than previously assumed, and bag size as a proxy for population density would then depend on the ability of hunters to adjust their effort according to population change. We speculate that this ability will depend on whether or not hunters have long‐term experience of a hunting area where they can return to hunt throughout the hunting season. We propose that recording hunting eff ort should be encouraged and possible correlations with game abundance and other factors such as weather should be investigated for game species.     

The Costs of Evaluating Species Densities and Composition of Snakes to Assess Development Impacts in Amazonia

Studies leading to decision-making for environmental licensing often fail to provide accurate estimates of diversity. Measures of snake diversity are regularly obtained to assess development impacts in the rainforests of the Amazon Basin, but this taxonomic group may be subject to poor detection probabilities. Recently, the Brazilian government tried to standardize sampling designs by the implementation of a system (RAPELD) to quantify biological diversity using spatially-standardized sampling units. Consistency in sampling design allows the detection probabilities to be compared among taxa, and sampling effort and associated cost to be evaluated. The cost effectiveness of detecting snakes has received no attention in Amazonia. Here we tested the effects of reducing sampling effort on estimates of species densities and assemblage composition. We identified snakes in seven plot systems, each standardised with 14 plots. The 250 m long centre line of each plot followed an altitudinal contour. Surveys were repeated four times in each plot and detection probabilities were estimated for the 41 species encountered. Reducing the number of observations, or the size of the sampling modules, caused significant loss of information on species densities and local patterns of variation in assemblage composition. We estimated the cost to find a snake as $ 120 U.S., but general linear models indicated the possibility of identifying differences in assemblage composition for half the overall survey costs. Decisions to reduce sampling effort depend on the importance of lost information to target-issues, and may not be the preferred option if there is the potential for identifying individual snake species requiring specific conservation actions. However, in most studies of human disturbance on species assemblages, it is likely to be more cost-effective to focus on other groups of organisms with higher detection probabilities.     

Use of SSCP to improve the efficiency of microsatellite identification from microsatellite‐enriched libraries

An inefficient aspect of marker identification from microsatellite‐enriched libraries is the proportion of clones with identical sequences. This can substantially increase the number of clones that need to be sequenced in order to identify a sufficient number of microsatellite loci. We propose the use of single‐stranded conformation polymorphism (SSCP) analysis to identify unique clones prior to sequencing. We used this approach prior to sequencing from microsatellite‐enriched libraries for three marine invertebrate species and were able to obtain a given number of unique clone sequences for only 28% of the sequencing effort that would have been required without SSCP screening.     

Species accumulation within land use and tree diameter categories in Burkina Faso,Mali, Niger and Senegal

Although farmers have managed west African parkland savanna systems for 1,000 of years, concerns have been raised about the sustainability of these agro-ecosystems due to human population growth, shortening of fallow periods, droughts, desertification and new orientations towards cash generation away from subsistence farming. We conducted a tree diversity survey in 16 villages from Burkina Faso, Mali, Niger and Senegal, recording total species composition for 300 quadrats (mainly 50 × 20 m²) that were randomly sampled from the main landuse categories of parklands of village fields (VF), bush fields (BF), sylvopastoral zone (SP) and forest reserves (FR). About 110 tree species were encountered, including 100 indigenous species. The results from balanced species accumulation curves (based on randomized subsampling of the same number of quadrats from each village) showed that the accumulated number of species was smallest in VF, largest in FR and almost equal in BF and SP, whereas classical (unbalanced) species accumulation curves yielded different results. Although there was a significant within-village reduction in species richness with increasing diameter class [averaging 8.5–13.1 more species in the smallest (<5 cm) compared to the largest diameter class (>80 cm)] for the different landuse categories, new species were also encountered in larger diameter classes (2.7–7.2 species). The evidence for tree regeneration problems (including problems in FR) suggest that farmer-managed tree regeneration should be further explored and that advances in domestication and marketing of indigenous tree species may be crucial to tree conservation in parkland systems.     

Abundance estimation of gray whale (Eschrichtius robustus) calves from shore‐based surveys undertaken near Ensenada,Baja California,Mexico, 2004–2006

Gray whale calf abundance was estimated from shore‐based surveys near Ensenada, Baja California, during their northbound migration. Over the course of 129 effort‐days (756.5 observation hours), 162 calves were counted, comprising 42, 41, and 79 calves in 2004, 2005, and 2006, respectively. To estimate the number of undetected calves during the observation periods in 2006, detection probabilities were estimated by simultaneous and independent counts using a Huggins model. The detection probabilities ranged from 0.655 to 0.997. The number of calves estimated during effort periods were divided by their estimated detection probabilities, while the total number of calves were estimated by fitting a generalized additive model (GAM) to the passage rate (whales/h) and effort (time) data. The final gray whale calf abundance estimates were 451 (95% CI = 430, 513), 253 (95% CI= 245, 308), and 442 (95% CI = 396, 510) calves for 2004, 2005, and 2006, respectively. The estimates were lower than those reported for Piedras Blancas, California, during the same years, with one possible reason being that an important number of cow/calf pairs migrate too far from shore (>10 km) to be detected from the observation site used in this research.     

Large-scale prediction of disulphide bridges using kernel methods, two-dimensional recursive neural networks, and weighted graph matching

The formation of disulphide bridges between cysteines plays an important role in protein folding, structure, function, and evolution. Here, we develop new methods for predicting disulphide bridges in proteins. We first build a large curated data set of proteins containing disulphide bridges to extract relevant statistics. We then use kernel methods to predict whether a given protein chain contains intrachain disulphide bridges or not, and recursive neural networks to predict the bonding probabilities of each pair of cysteines in the chain. These probabilities in turn lead to an accurate estimation of the total number of disulphide bridges and to a weighted graph matching problem that can be addressed efficiently to infer the global disulphide bridge connectivity pattern. This approach can be applied both in situations where the bonded state of each cysteine is known, or in ab initio mode where the state is unknown. Furthermore, it can easily cope with chains containing an arbitrary number of disulphide bridges, overcoming one of the major limitations of previous approaches. It can classify individual cysteine residues as bonded or nonbonded with 87% specificity and 89% sensitivity. The estimate for the total number of bridges in each chain is correct 71% of the times, and within one from the true value over 94% of the times. The prediction of the overall disulphide connectivity pattern is exact in about 51% of the chains. In addition to using profiles in the input to leverage evolutionary information, including true (but not predicted) secondary structure and solvent accessibility information yields small but noticeable improvements. Finally, once the system is trained, predictions can be computed rapidly on a proteomic or protein-engineering scale. The disulphide bridge prediction server (DIpro), software, and datasets are available through www.igb.uci.edu/servers/psss.html.     

Designing occupancy surveys and interpreting non‐detection when observations are imperfect

Aim Conservation practitioners use biological surveys to ascertain whether or not a site is occupied by a particular species. Widely used statistical methods estimate the probability that a species will be detected in a survey of an occupied site. However, these estimates of detection probability are alone not sufficient to calculate the probability that a species is present given that it was not detected. The aim of this paper is to demonstrate methods for correctly calculating (1) the probability a species occupies a site given one or more non‐detections, and (2) the number of sequential non‐detections necessary to assert, with a pre‐specified confidence, that a species is absent from a site. Location Occupancy data for a tree frog in eastern Australia serve to illustrate methods that may be applied anywhere species’ occupancy data are used and detection probabilities are < 1. Methods Building on Bayesian expressions for the probability that a site is occupied by a species when it is not detected, and the number of non‐detections necessary to assert absence with a pre‐specified confidence, we estimate occupancy probabilities across tree frog survey locations, drawing on information about where and when the species was detected during surveys. Results We show that the number of sequential non‐detections necessary to assert that a species is absent increases nonlinearly with the prior probability of occupancy, the probability of detection if present, and the desired level of confidence about absence. Main conclusions If used more widely, the Bayesian analytical approaches illustrated here would improve collection and interpretation of biological survey data, providing a coherent way to incorporate detection probability estimates in the design of minimum survey requirements for monitoring, impact assessment and distribution modelling.